Outlook: Newsletter of the Society of Behavorial Medicine

Spring 2022

Transforming Digital Behavioral Health Interventions to Address Inequities: A Working Group’s Mission

Maura Kepper, PhD, MPH; Abdul Shaikh, PhD, MHSc; Sophy Perdomo, PhD; Amber Blackwood, MPH; Kassandra Alcaraz, PhD, MPH; and Lisa Klesges, PhD, MS; Behavioral Informatics and Technology (BIT) SIG

COVID-19, the first global pandemic of the digital age, has ignited and spurred a rapid emergence of digital health interventions.1 This pandemic has demonstrated the potential of digital health to improve the quality, efficiency, consistency, and availability of care including behavioral interventions, but has also revealed challenges and equity concerns.2-5 Digital health encompasses a range of technologies including “mobile health (mHealth), health information technology (HIT), wearable devices, telehealth and telemedicine, and personalized medicine.”6 Inequities in access to, and implementation and sustainability of these tools, as well as the quality of care afforded by digital technology, can reinforce and even deepen the inequities that have long existed among the most vulnerable patients and communities.1 A working group was formed across the Behavioral Informatics and Technology and Health Equity Special Interest Groups (SIGs) to articulate a behavioral medicine perspective to inform use-inspired research for digital health equity.7 The group consists of behavioral scientists spanning academia, industry, and nonprofits with expertise in a broad range of disciplines that include informatics, health services research, dissemination & implementation science, and health disparities research.

We began by cataloguing challenges of equitably implementing and sustaining digital health technologies to promote healthy behaviors among diverse populations and settings, drawing from our diverse expertise and existing theories, frameworks, and models8,9 focused on health equity, technology, and dissemination and implementation (e.g., the ConNECT Framework,10 the Health Equity Implementation Framework, 11 and the Integrated Technology Implementation Model).12 We organized our efforts into three working groups that will advance the field by: 1) contributing to the peer-reviewed scientific literature; 2) developing guidelines and tools for practitioners; and 3) advocating for relevant policy change. Each group will address major challenges such as development that has occurred predominately among homogenous, highly socioeconomically advantaged populations,7 and thereby failed to account for cultural differences (e.g., languages), various reading levels, and environments. Our group may generate guidelines for participatory design that engages end-users and stakeholders (e.g., payers, administrators) that are necessary for equitable end-user adoption, utilization, and productivity. Furthermore, the development and validation of digital health tools, especially those involving artificial intelligence and machine learning, require investments in datasets that are representative of the target population. We will focus beyond design and consider challenges with access and implementation. Digital literacy and internet connectivity are the major determinants of access,13 yet, we must not overlook less visible factors (e.g., knowledge of resources, access to educational resources, technology support, affordability, insurance coverage) that may be solved by strategies that are more feasible (e.g., less expensive, within an organization). These challenges extend beyond the initial adoption of digital health tools and have critical implications for equitable sustainability and impact.3,14,15 Evaluation and the use of data to understand if we are increasing inequities should inform iterations in real time to improve usability, effectiveness, and equity. Furthermore, users should be provided access to their own data so that they may contribute to making digital health solutions more relevant safe, effective, and equitable.

We are working on: 1) an opinion piece on “Digital Health Equity for Behavior Change”; 2) a review of frameworks/methods of cultural adaption of digital behavioral interventions; 3) a policy brief focused on leveraging technology to support child nutrition, increase access to food assistance programs (WIC & SNAP), and reduce obesity inequities among underserved populations. We invite you to join us by emailing Maura Kepper at kepperm@wustl.edu.



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  2. Smith AJ, Skow Á, Bodurtha J, Kinra S. Health Information Technology in Screening and Treatment of Child Obesity: A Systematic Review. Pediatrics. 2013;131(3):e894-e902.
  3. Payne PRO, Lussier Y, Foraker RE, Embi PJ. Rethinking the role and impact of health information technology: informatics as an interventional discipline. BMC Med Inform Decis Mak. 2016;16:40-40.
  4. Zhang X, Hailu B, Tabor DC, et al. Role of health information technology in addressing health disparities: Patient, clinician, and system perspectives. Medical care. 2019;57 Suppl 6 Suppl 2(Suppl 6 2):S115-s120. PMC6589829.
  5. Coleman KJ, Hsii AC, Koebnick C, et al. Implementation of Clinical Practice Guidelines for Pediatric Weight Management. The Journal of Pediatrics. 2012;160(6):918-922.e911.
  6. Administration USFaD. What is Digital Health? . Digital Health Center of Excellence Web site. https://www.fda.gov/medical-devices/digital-health-center-excellence/what-digital-health. Published 2020. Accessed 2/7/2022.
  7. Lyles CR, Wachter RM, Sarkar U. Focusing on Digital Health Equity. Jama. 2021;326(18):1795-1796.
  8. Soobiah C, Cooper M, Kishimoto V, et al. Identifying optimal frameworks to implement or evaluate digital health interventions: a scoping review protocol. BMJ Open. 2020;10(8):e037643.
  9. Tabak RG, Khoong EC, Chambers DA, Brownson RC. Bridging research and practice: models for dissemination and implementation research. Am J Prev Med. 2012;43(3):337-350.
  10. Alcaraz KI, Sly J, Ashing K, et al. The ConNECT Framework: A model for advancing behavioral medicine science and practice to foster health equity. Journal of behavioral medicine. 2017;40(1):23-38.
  11. Woodward EN, Matthieu MM, Uchendu US, Rogal S, Kirchner JE. The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment. Implementation Science. 2019;14(1):26.
  12. Schoville R, Titler MG. Integrated Technology Implementation Model: Examination and Enhancements. CIN: Computers, Informatics, Nursing. 2020;38(11):579-589.
  13. Sieck CJ, Sheon A, Ancker JS, Castek J, Callahan B, Siefer A. Digital inclusion as a social determinant of health. npj Digital Medicine. 2021;4(1):52.
  14. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ (Clinical research ed). 2005;330(7494):765. PMC555881.
  15. Koppel R, Kreda DA. Healthcare IT usability and suitability for clinical needs: challenges of design, workflow, and contractual relations. Studies in health technology and informatics. 2010;157:7-14.